The business of enterprises has rapidly expanded with the explosive increase of data and appearance of various environments and platforms. With the advent of a new business environment, more efficient and flexible processing of a data service and information and a more efficient and flexible data management function are required. According to such a change, research into a database for solving problems in high performance, high availability and extensibility which are the basis of enterprise business implementation has continued.
In a database management system (DBMS), data can be stored in a data storage. In a relational database management system (RDBMS), the data storage may be designated as a table. The table can include one or more rows and each of one or more rows can include one or more columns.
When the database includes a large quantity of data or a large capacity of data is stored in the database, a relatively long time can be required for performing a query for retrieving data in which a user has an interest. When a lot of time is required for the database to respond to the query, a bad influence can be exerted on performance of the database.
Large-capacity objects in the DBMS in the related art are stored as a large object (LOB) or binary large object (BLOB) data type in order to overcome a limit for an excessively large capacity. However, as disclosed in U.S. Pat. No. 8,756,261, only LOB or BLOB metadata is stored in a relational table and the LOB or BLOB data cannot but be stored outside the table as a separate file type.
A pivot calculation is performed in order to extend a schema by performing an aggregation query with respect to a specific condition in the DBMS in the related art. When the pivot calculation is performed, since multiple pivot columns are additionally automatically generated, there are difficulties such as the need for modifying a complicated SQL statement, and the like in order for the user to perform the additional calculation by using the multiple pivot columns.